Home leaving trajectories in Canada: exploring cultural and gendered dimensions
Bibliographic record
Abstract
In this exploratory study, we profile variations in home leaving, home returning, and home staying behaviour among four ethnocultural groups in Canada - British, Chinese, Indian, and South European. Data collected in a 1999-2000 survey of 1,907 young adults (ages 19-35) residing in the Vancouver area are used. Our principal foci are ethnocultural and gendered aspects of home leaving trajectories, specifically: ages at home leaving and returning, and reasons for home leaving, home returning and home staying. Special attention is paid to returners/boomerangers, given an increasing overall trend in home returning in Canada. We find that: (a) both ethnocultural origin and gender are important determinants of home leaving trajectory, (b) there is a distinct (but far from tidy) difference between European-origin and Asian-origin groups in home leaving trajectory, (c) British-Canadians leave home at the youngest ages and Indo-Canadians at the oldest ages, (d) the main reason for home leaving is independence for British-Canadians; schooling for Chinese-Canadians, and marriage for Indo-Canadians, (e) among all four groups, home returners leave home initially at younger ages and, with the exception of Indo-Canadian young men, who typically leave home for school, and (f) gender differences in home leaving trajectory are larger among the Chinese and Indo-Canadians than among persons of European origins. Overall, we conclude that the theorized trend of the individualized family life course holds for only some ethnocultural groups in Canada. We conclude with suggestions for future research directions on the topic of ethnicity and the home leaving life course transitions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".